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function DynareResults = initial_estimation_checks(objective_function,xparam1,DynareDataset,Model,EstimatedParameters,DynareOptions,BayesInfo,DynareResults)
% function initial_estimation_checks(xparam1,gend,data,data_index,number_of_observations,no_more_missing_observations)
% Checks data (complex values, ML evaluation, initial values, BK conditions,..)
%
% INPUTS
% xparam1: vector of parameters to be estimated
% gend: scalar specifying the number of observations
% data: matrix of data
%
% OUTPUTS
% DynareResults structure of temporary results
%
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2012 Dynare Team
%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
if DynareDataset.info.nvobs>Model.exo_nbr+EstimatedParameters.nvn
error(['initial_estimation_checks:: Estimation can''t take place because there are less declared shocks than observed variables!'])
end
if DynareDataset.info.nvobs>find(diag(Model.Sigma_e))+EstimatedParameters.nvn
error(['initial_estimation_checks:: Estimation can''t take place because too many shocks have been calibrated with a zero variance!'])
end
% check if steady state solves static model (except if diffuse_filter == 1)
[DynareResults.steady_state] = evaluate_steady_state(DynareResults.steady_state,Model,DynareOptions,DynareResults,DynareOptions.diffuse_filter==0);
% Evaluate the likelihood.
[fval,junk1,junk2,a,b,c,d] = feval(objective_function,xparam1,DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults);
if DynareOptions.dsge_var || strcmp(func2str(objective_function),'non_linear_dsge_likelihood')
info = b;
else
info = d;
end
% if DynareOptions.mode_compute==5
% if ~strcmp(func2str(objective_function),'dsge_likelihood')
% error('Options mode_compute=5 is not compatible with non linear filters or Dsge-VAR models!')
% end
% end
if isnan(fval)
error('The initial value of the likelihood is NaN')
elseif imag(fval)
error('The initial value of the likelihood is complex')
end
if info(1) > 0
disp('Error in computing likelihood for initial parameter values')
print_info(info, DynareOptions.noprint)
end
if any(abs(DynareResults.steady_state(BayesInfo.mfys))>1e-9) && (DynareOptions.prefilter==1)
disp(['You are trying to estimate a model with a non zero steady state for the observed endogenous'])
disp(['variables using demeaned data!'])
error('You should change something in your mod file...')
end
disp(['Initial value of the log posterior (or likelihood): ' num2str(-fval)]);
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